A few recent papers showed that deep convolutional networks struggle to learn features integrating large spatial domains.
For instance [1]} showed that the receptive field size of a deep CNN is smaller than the sum of its kernel sizes.
[2]}, [3]} showed that ImageNet-trained ResNet relies on small image patches and textures, rather than object shapes, and does not transfer well to stylised images.
[4]} showed that ResNet struggles on the Pathfinder challenge, a simple task that requires integrating features over long distances.
